Robot Dynamics and Control

This course provides the basics for deriving kinematic/dynamical models of a robot (such as a factory robotic arm, mobile robot, etc.) and for designing corresponding robot controllers. Students will learn how to derive the equations of motion and basic control equations themselves, and they will also learn how to use existing frameworks to do the same.

THEORY SUBJECTS

Introduction and Fundamentals

• Course layout, instructors, grade scheme, etc.

• Importance of the course and the big picture

• Connection to the real world

• Basic concepts/terms in robotics

• Methods to describe robot pose

• Numerical integration

Recap of Control Theory

• State-space model

• Root locus

• Bode plots

• PID control

• Concept of LQR and MPC control

• Reference to online materials

Endpoint Control for Robotic Manipulators

• Big picture + motivation

• Difference between robots with position and torque-controlled motors

• Endpoint position control (with a PID controller)

• Endpoint impedance control (for position tracking tasks)

• Endpoint force control (for force tracking tasks)

Robotic Arm Kinematics

• Deriving forward kinematics and Jacobian (for a 2-DoF planar arm)

• Transformations between the endpoint and the joint space using the Jacobian

• Kinematic singularities and their solution

• Kinematic redundancy and task priority control (for a 4-DoF planar arm)

• Kinematics of parallel robots and differences compared to serial robots

Robotic Arm Dynamics

• Rigid-body dynamics model

• Deriving a dynamics model with the Lagrange method for a 2-DoF planar arm

• Using the dynamics model in the control

• Dynamic task priority control

3D Robotic Arm

• Deriving 3D kinematics using the Denavit-Hartenberg convention

• 3D trajectory generation

Planning and Motion Control

• Trajectory planning

• Orientation control

Kinematics and Dynamics of Mobile Robot / Automated Vehicle

• Forward kinematic models

• Wheel kinematic constraints

• Robot kinematic constraints

• Non-holonomic system

• Derivation of linear bicycle model

• Steady-state analysis

Dynamics and Control of Mobile Robot / Automated Vehicle

• Transient analysis

• Frequency response

• Path-following control

PRACTICAL ASSIGNMENTS (individual)

• Assignment 1:
  The goal of this assignment is to learn how to control a 2-DoF robotic arm in Python to follow a prescribed trajectory using kinematic and dynamic equations.

• Assignment 2:
  The goal of this assignment is to learn how to control a multi-DoF robotic manipulator (3D kinematics, 3D trajectory, orientation control).

• Assignment 3:
  The goal of this assignment is to learn how to implement a linear bicycle model, and calculate and discuss primary handling characteristics, poles, stability analysis, and feedback control (PID).